True. I should have clarified that the workaround used for many NLP tasks, utilizing libs such as Langchain, will become obsolete. And after further thought, obsolete is wrong. More likely just used for more niche needs within NLP.
The GPT-4 paper even has an example of this exact approach. See section 2.10:
The red teamer augmented GPT-4 with a set of tools:
• A literature search and embeddings tool (searches papers and embeds all text in vectorDB,
searches through DB with a vector embedding of the questions, summarizes context with LLM,
then uses LLM to take all context into an answer)
• A molecule search tool (performs a webquery to PubChem to get SMILES from plain text)
• A web search
• A purchase check tool (checks if a SMILES21 string is purchasable against a known commercial
catalog)
• A chemical synthesis planner (proposes synthetically feasible modification to a compound, giving
purchasable analogs)
Quite the contrary. Utilising such libs makes GPT-4 even more powerful to enable complex NLP workflows which will likely be a majority of real business use cases in the future.
